Are nitrogen and carbon cycle processes impacted by common stream antibiotics? A comparative assessment of single vs. mixture exposures.

A variety of antibiotics are ubiquitous in all freshwater ecosystems that receive wastewater. A wide variety of antibiotics have been developed to kill problematic bacteria and fungi through targeted application, and their use has contributed significantly to public health and livestock management. Unfortunately, a substantial fraction of the antibiotics applied to humans, pets and livestock end up in wastewater, and ultimately many of these chemicals enter freshwater ecosystems. The effect of adding chemicals that are intentionally designed to kill microbes, on freshwater microbial communities remains poorly understood. There are reasons to be concerned, as microbes play an essential role in nutrient uptake, carbon fixation and denitrification in freshwater ecosystems. Chemicals that reduce or alter freshwater microbial communities might reduce their capacity to degrade the excess nutrients and organic matter that characterize wastewater. We performed a laboratory experiment in which we exposed microbial community from unexposed stream sediments to three commonly detected antibiotics found in urban wastewater and urban streams (sulfamethoxazole, danofloxacin, and erythromycin). We assessed how the form and concentration of inorganic nitrogen, microbial carbon, and nitrogen cycling processes changed in response to environmentally relevant doses (10 μg/L) of each of these antibiotics individually and in combination. We expected to find that all antibiotics suppressed rates of microbial mineralization and nitrogen transformations and we anticipated that this suppression of microbial activity would be greatest in the combined treatment. Contrary to our expectations we measured few significant changes in microbially mediated functions in response to our experimental antibiotic dosing. We found no difference in functional gene abundance of key nitrogen cycling genes nosZ, mcrA, nirK, and amoA genes, and we measured no treatment effects on NO3- uptake or N2O, N2, CH4, CO2 production over the course of our seven-day experiment. In the mixture treatment, we measured significant increases in NH4+ concentrations over the first 24 hours of the experiment, which were indistinguishable from controls within six hours. Our results suggest remarkable community resistance to pressure antibiotic exposure poses on naïve stream sediments.

Introduction

Pharmaceuticals are classified as “new emerging pollutants”, due to their detection in almost all environmental matrices at increasing concentrations and no regulations regarding their release into the environment [1-3]. Organisms in urban streams are exposed to a suite of chemicals via wastewater and receive among the highest diversity of pharmaceuticals, which may be sourced from septic fields, leaky sewage infrastructure, combined sewer overflows, wastewater treatment plant effluent, and pet waste [4-9]. Of the various types of pharmaceuticals antibiotics are the most frequently used and detected in aquatic environments [2, 10].

Antibiotics may compound the effects of excess nutrient loading and more frequent scouring flows that are known to reduce the capacity for urban stream ecosystems to support biodiversity and to sequester or transform excess nutrients [5, 11, 12]. Antibiotics are manufactured to inhibit or kill microbes at the point of use, but because they continue to be in their active form in wastewater, they can have unintended negative consequences in receiving ecosystems [13]. Microbes are principally responsible for the transformation and assimilation of excess nitrogen (N) in urban streams (e.g., denitrification, nitrogen fixation, and organic matter decomposition) [14-16]. If antibiotics alter benthic microbial communities, this may result in significant changes to these critical N processing function. Excessive reactive N in streams can cause eutrophication, harmful algal blooms, oxygen depletion, and acidification [17-20]. Recent experimental evidence has demonstrated that pharmaceuticals can suppress processes such as primary production and respiration [21-23]. There has been little experimental work examining the effects of pharmaceuticals on N cycling, but it has been shown that the antibiotic sulfamethoxazole can inhibit denitrification [24, 25].

In previous work, we found that sulfamethoxazole, danofloxacin, and erythromycin were the most commonly detected antibiotics in streams in the Piedmont of North Carolina [7, 26, 27]. These commonly detected antibiotics each represent a different class and mode of action regarding bacterial death or inhibition. Erythromycin and sulfamethoxazole are both broad spectrum antibiotics that are widely used for human and veterinary purposes. Both compounds inhibit growth but do so through different mechanisms. Erythromycin is a macrolide antibiotic that irreversibly binds to 50S ribosomal subunits [28], while sulfamethoxazole is a sulfonamide that inhibits nucleic acid, protein synthesis, and cell wall permeability [29]. Danofloxacin is a synthetic fluoroquinolone that is primarily used in veterinary medicine for the treatment of respiratory disease. Danofloxacin inhibits DNA replication by deactivation of bacterial DNA gyrase and topoisomerase IV [30]. Prior studies in the same region measured low rates of N removal and high methane concentrations in streams with detectable concentrations of these three antibiotics [31, 32].

Studies investigating the effects emerging contaminants have on ecosystem function lag behind other well-defined drivers of global environmental change [13]. The objective of this study was to assess how stream sediment biogeochemistry and microbial activity would change in response to dosing with relevant concentrations of these three common antibiotic pollutants. In our experiment, each antibiotic was added alone or in combination to a sediment slurry. We measured changes in the concentration of NH4+, NO3-, N2, N2O, CH4, and CO2 over the course of 7 days (24 hours for NH4+ and NO3-) following the experimental dosing using destructive sampling of replicates at multiple time steps. All replicates were fully oxygenated at the start of the experiment, and all slurries were hypoxic/anoxic within 24 hours, allowing us to examine the impact of our antibiotic dosing under fluctuating redox conditions. We expected to find that all antibiotic treatments would lead to declines in the assimilation and transformation of one or more forms of inorganic N and organic C relative to the controls. We anticipated measuring the greatest number and magnitude of impacts in our antibiotic mixture treatment, predicting that the effects of the three antibiotics would be antagonistic, additive, or synergistic due to their divergent modes of action.

Materials and methods

Sample collections

Sediment and surface water used in microcosm construction were collected from a forested stream near Lake Brandt in Greensboro, NC, USA (36.173262, -79.83790) (Table 1). Previous surveys of this site found no antibiotic residues in compartments sampled. Surface water was collected in 5 L acid-washed carboys, and sediment was collected on-site and transferred into sterile Ziploc® plastic bags. At the sampling site, pH, dissolved oxygen, and conductivity were recorded. Once transported to the lab, surface water was filtered using 0.7 μm GF/F filters. Sediments were homogenized and stored on ice in the dark until microcosm construction. Surface water samples were stored in a refrigerator at 4°C. In the laboratory, ash-fry dry mass and sediment particle size classification were determined from subsamples (Table 1; S1 File). Subsamples of surface water was analyzed on a Lachat QuickChem 8500 automated system (Lachat Instruments, Loveland, Colorado, USA) to determine background concentrations of NH4+ and NO3- (Table 1).

Table 1

Site data for surface water and sediment used in the study.

Site	Lat	Long	pH	DO (mg/L)	Conductivity (μS/cm)	Temperature (°C)	NH4+ (μg N L-1)	NO3- (μg N L-1)	% Organic Matter
Lake Brandt	36.173262	-79.8379	8.7	4.8	555	23°C	18.2	116	1.2

Antibiotic solutions

Sulfamethoxazole (SMX), danofloxacin (DAN), and erythromycin (ETM) (all > 98% purity) were obtained from Sigma-Aldrich (St. Louis, MO) (Table 2). Stock solution (1 mg/L) was added to filtered surface water to yield an initial concentration of 10 μg/L for each antibiotic treatment. Mixture treatments consisted of each antibiotic having an initial concentration of 10 μg/L.

Table 2

Antibiotic information of those used in the present study.

Antibiotic	Class	Mode of Action	CAS No.	pKa	LogKow
Sulfamethoxazole (SMX)	Sulfonamide	Inhibiting nucleic acids, protein synthesis, and folic acid synthesis	723-46-6	1.6, 5.7	0.89
Danofloxacin (DAN)	Fluoroquinolone	Inhibition of bacterial DNA replication	112398-08-0	6.22, 9.43	0.44
Erythromycin (ETM)	Macrolide	Prevents growth by binding irreversibly to 50S ribosomal subunits	114-07-8	7.7, 8.9	1.6–3.1

Microcosm construction

Microcosms consisted of 200 mL glass serum bottles. Bottles contained 100 g of wet naïve sediments and 100 mL of filtered surface water. Control treatments contained no spiked antibiotic solution. Microcosms were sealed with gas impermeable butyl rubber stoppers and crimped aluminum seals (Geo-Microbial Technologies). All microcosms were spiked with a nutrient enrichment to reduce substrate limitations. Enrichments consisted of glucose (0.2 g C), sodium acetate (0.12 g C), and ammonium chloride (0.16 mg N). Enrichments were mixed with filtered stream water prior to the addition of antibiotics. The treatments (control, SMX, DAN, ETM, and SMX+DAN+ETM mixture) were further divided into separate oxic and hypoxic or anoxic treatments. After antibiotics solutions (10 μg/L) were spiked into the respective microcosm and sealed, microcosms were shaken. Samples collected for the oxic treatments consisted of 3 replicates per treatment per time point (n = 12 per antibiotic treatment), where the same microcosm was sampled repeatedly with samples collected at 0, 6, 12, and 24 h.

Microcosms were allowed to go hypoxic or anoxic naturally without amending or purging them with N2. Preliminary sediment oxygen demand studies conducted in the lab showed dissolved oxygen levels reached 0.5 mg/L by 24 h (S2 File). The oxygen demand study concluded at 24 h, while samples taken during the hypoxic or anoxic period were collected past this time. Calculated oxygen saturation levels from 0 to 24 h were ≥ 5.5%. Following 24 h, we suspect that oxygen levels were ≤ 5.5%. It is important to note that in homogeneous sediments, methanogen activity and denitrification can be confined to anoxic microsites within sediments [33]. Due to this, even in the presence of oxygen, these processes can still occur. Microcosms designated to become hypoxic or anoxic naturally were sampled over 7 days, with sampling occurring on days 2, 4, and 7. Each treatment consisted of five replicates per time point (n = 25). Due to the nature of sampling, serum bottles were destructively sampled with five randomly selected bottles at each sampling point per treatment (n = 125). All microcosms were stored in the dark to limit photodegradation of antibiotics throughout the study period. Antibiotic concentration in water or sediment were not measured at the conclusion of the study.

NH4+ and NO3- measurements

NH4+ and NO3- concentrations were analyzed over 24 h. At each specified sampling point (0, 6, 12, and 24 h), 10 mL of water was collected. Water was collected from the same bottle at each time point and filtered through ashed GF/F filters. Water was not replaced as it might alter microcosm conditions at subsequent sampling periods (increased DO, dilution). Samples were then kept in a -20°C freezer until analysis. At the conclusion of the study, samples were analyzed on the Lachat QuickChem 8500 automated system (Lachat Instruments, Loveland, Colorado, USA) to determine NH4+ and NO3- concentrations. NH4+ and NO3- concentrations were calculated over time to determine rate of consumption over 24 h (μg N L-1 hour.).

N2O, CH4, and CO2 measurements

Greenhouse gas or GHG (N2O, CH4, CO2) concentrations were measured over 7 days, with sampling times on day 2, 4, and 7. Each sample was collected from the gaseous headspace following shaking the bottles to release any gas trapped within sediment. 10 mL of headspace gas was extracted and transferred to a 9 mL glass vial. Glass vials containing headspace gas were purged with N2 and evacuated prior to use. Gas samples were stored inverted in the dark until sample analysis. N2O, CH4, and CO2 concentrations were measured using a Teledyne Tekmar 7000 headspace autosampler (Teledyne Tekmar, Mason, Ohio, USA) to inject samples into a Shimadzu GC-17A ver.3 gas chromatograph with a Porapak Q column and electron capture detector [34]. Concentrations were acquired from NIST grade calibration standards. The linearity of the calibration was determined from the R2 > 0.97. Concentrations of N2O, CH4, and CO2 were normalized to the dry weight of sediment (g) (nmol g-1 DW). Dry-weight concentrations were plotted over time for each microcosm to estimate the rate of gas production (nmol g-1 DW day-1).

N2 measurements

N2 was measured using a Membrane Inlet Mass Spectrometer or MIMS to determine dissolved N2 and Ar concentrations in surface water overlaying sediment. Serum bottles (n = 25/time point) were destructively sampled due to the use of the MIM probe. Standards for N2 concentrations (humid-atmosphere-equilibrated deionized water stirring in high-precision water baths) at 22°C and 24°C were run every six samples. Standards were run in triplicate along with samples collected at day 2,4, and 7. N2 concentrations were achieved using the MIMS_gasfunction package in R version 3.5.2 (R Core Team 2017). N2 concentrations were converted from mg/L to μmol/g and normalized to dry weight of sediment (g). Dry-weight concentrations were plotted over time for each microcosm to estimate the rate of N2 production (μmol g-1 DW day-1).

Functional gene abundance

We measured the abundance of key genes necessary for biochemical processes evaluated in the present study. We measured 16s rRNA, nosZ (encodes for nitrous oxide reductase), mcrA (encodes the alpha subunit of the methyl-coenzyme M reductase (MCR), which catalyzes the last step in methanogenesis), nirK (encodes for the copper-containing nitrite reductase), and amoA (encodes for ammonia monooxygenase) [34-36] (Table 3). At the conclusion of the study, subsamples of sediment were stored in -20°C freezer in LifeGuard Soil Preservation Solution (Qiagen) until extraction. We extracted DNA from sediments in triplicate with PowerSoil DNA Isolation kits (MoBio Laboratories, Carlsbad, California, USA). DNA was quantified by a Nanodrop Spectrophotometer (Thermo Scientific) at an absorbance of 260 nm. Following extraction, samples were diluted to 3 ng/mL. Genes of interest DNA were amplified using primers purchased from Integrated DNA Technologies (Coralville, Iowa, USA) (Table 3) and iTaq Universal SYBR mix (Bio-Rad Laboratories, Hercules, California, USA). The average efficiency of the qPCR reaction ranged from 81% to 111%, all standard curves had R2 values ≥0.98 (Table 3). Copies were normalized to the amount of extracted sediment.

Table 3

Primers used in the functional gene abundance qPCR assay.

Gene	Forward Sequence	Reverse Sequence		Product size (bp)	Efficiency	Reference
16s rRNA	5’-TAA CCT GGG AAC GCG ATT T-3’		5’- CCA CTA CCC TCT ACC ACA CT-3’	55	111%	[37]
nosZ	5’- AGA ACG ACC AGC TGA TCG ACA-3”		5’- TCC ATG GTG ACG CCG TGG TTG-3’	300	101%	[38]
mcrA	5’- AAA GTG CGG AGC AAT CAC C-3’		5’TCG TCC CAT TCC TGC TGC ATT GC-3’	186	87%	[39]
nirK	5’-TCA TGG TGC CGC GGA CGG-3’		5- GAA CTT GCC GGT GCC CAG AC-3’	326	88%	[40]
amoA	5’- GGG GTT TCT ACT GGT GGT-3’		5-‘ CCC CTC BGS AAA VCC TTC TTC-3’	491	81%	[41]

Statistical analysis

Due to non-normal distribution throughout the dataset, non-parametric analyses were conducted. Outlier analysis was performed in Microsoft Excel to determine the upper and lower bounds. The upper and lower bounds were calculated using the following equations:

Q3 + (1.5 * IQR) and Q1 - (1.5 * IQR)

Q1 = Quartile 1

Q3 = Quartile 3

IQR = Interquartile Range

For each respective assay, a Kruskal-Wallace test compared experimental treatments change in concentration to the control to determine differences. For rate analysis, NH4+ and NO3- concentrations were plotted over time (24 hours) for each microcosm (μg N L-1 hour). N2O, N2, CH4, and CO2 rates were assessed by plotting concertation across time (7 days) for each microcosm (nmol g-1 DW d-1 or μmol g-1 DW d-1). A Pairwise Wilcox test was run to determine distinct differences in significant treatments. Gene copy numbers were compared using Kruskal-Wallace test to determine differences among treatments. Correlation analysis was conducted between gene copy number and respective products and reactants. Data were analyzed using R Studio (3.5.2) and graphs were made in GraphPad Prism (8.5.1).

Results

Oxic period

NH4+ and NO3-

NH4+ and NO3- concentrations from our collection site near Lake Brandt were 18.2 and 116 μg N L-1, respectively (Table 1). We spiked our microcosms with 1 mg/L of NH4Cl or 0.16 mg N. At the start of the experiment NH4+ concentrations ranged between 388 to 673 μg N L-1 ± 49.12 ( ± 95%CI) and NO3- concentrations ranged from 166 to 281 μg N L-1 ± 16.67 ( ± 95%CI) across all treatments (Fig 1A, 1C; S3 File). Mean DAN NH4+ concentration at 0 h were exceptionally high (1330 ±178 μg N L-1) ( ± SE) compared to the other treatments and were identified as statistical outliers (Fig 1A), so rate calculations for this treatment were only calculated at the second sampling point.

Fig 1

Mean ± SE dissolved (A) NH4+, (C) NO3- concentrations in microcosms plotted across time (0,6,12, and 24 hour) and whisker plots (min to maximum) of the change in (B) NH4+ and (D) NO3- concentration from microcosms exposed to control and experimental treatments. Identical letters above bars (1B and 1D) indicate treatments that are not significantly different as determined by post hoc Pairwise Wilcox Test, while different letters indicate rates that are significantly different.

In the controls, NH4+ concentration declined over a 24 h period from 459 ± 46 to 33 ± 9.4 μg N L-1 h-1 ( ± SE) (Fig 1A), with a rate of depletion of -19.2 ± 1.6 μg N L-1 h-1 ( ± SE). There was no detectable difference between the control, DAN, and ETM treatments, while NH4+ concentration remain unchanged in the SMX treatment (0.13 ± 1.6 μg N L-1 h-1) ( ± SE), but increased significantly in the mixture treatment (11.5 ± 0.7 μg N L-1 h-1) ( ± SE), over the course of the 24 h oxic assay (Fig 1A, 1B; Table 4).

Table 4

Mean ± SE consumption and production rates of nitrogen species (NH4+, NO3-, N2, N2O), CH4, and CO2.

	μg N L-1 h-1		μmol g-1 DW d-1	nmol g-1 DW d-1
	NH4+	NO3-	N2	N2O	CH4	CO2
Control	-19.2 ± 1.6	-6.7 ± 0.5	-0.05 ± 0.21	-0.001 ± 0.0002	6.3 ± 0.8	20.4 ± 24.0
SMX+DAN+ETM	11.5 ± 0.7*	-4.9 ± 0.6	0.31 ± 0.25	-0.001 ± 0.0001	3.3 ± 1.0	66.0 ± 2.9
SMX	0.13 ± 1.6*	-6.4 ± 0.4	-0.45 ± 0.12	-0.0004 ± 0.0001	3.7 ± 0.6	68.4 ± 11.4
DAN	-12.8 ± 7.7	-6.3 ± 0.3	-0.36 ± 0.60	-0.001 ± 0.0003	6.4 ± 1.3	47.5 ± 23.7
ETM	-18.65 ± 3.1	-6.3 ± 0.3	0.28 ± 0.44	-0.001 ± 0.0003	7.5 ± 1.6	40.4 ± 14.8

*denotes treatments that were significantly different than control treatment.

Mean NO3- concentration from the control treatment (166 ± 9) ( ± SE), was 1.4 to 4.3 times lower than single and mixture antibiotic treatments at 0 h (p<0.05: Fig 1C; S3 File). By 24 h, NO3- concentrations from each treatment had declined compared to concentrations at 0 h (Fig 1C). The rate of decline in NO3- concentration ranged from -4.7 to -6.7 μg N L-1 h-1 (Fig 1D; Table 4) where no treatments differed from the control treatment (p>0.05; Fig 1D; Table 4).

Hypoxic or anoxic period

N2O

Our initial recordings of N2O concentrations 0.009 to 0.014 nmol g-1 DW ± 0.001 ( ±95%CI) at day 2 found there was no difference among treatments when compared to the control (Fig 2A; S4 File). This trend was consistent at day 4 and 7 where there was no difference, despite each treatment declining in concentration (p>0.05; Fig 2A; S4 File). Control rate of N2O production was not significantly different than the other treatments used in the study with the mean rate of N2O production ranging from -0.0004 to -0.001 nmol g-1 DW d-1 (p>0.05 Fig 2B; Table 4).

Fig 2

Mean ± SE dissolved (A) N2O, (C) N2 concentrations in microcosms plotted across time (Day 2, 4, and 7) and whisker plots (min to maximum) of the rate of production for (B) N2O and (D) N2 from microcosms exposed to control and experimental treatments.

N2 concentrations (16.8 to 20 μmol g-1 DW ± 0.65) ( ±95%CI) measured at day 2 were not significantly different among treatment (p>0.05; Fig 2C; S4 File). At day 4, control and mixture treatment concentrations were 1.2 to 1.5 times lower than the SMX, DAN, and ETM treatments (p<0.05; S4 File; Fig 2C). By day 7, N2 concentrations were not significantly different among treatments (p>0.05; Fig 2C, S4 File). The rate of N2 production ranged between -0.05 to 0.31 μmol g-1 DW d-1, where we observed no significant difference among treatments. (Fig 2D; S4 File).

CO2

Mean CO2 concentrations at day 2 ranged from 322 to 592 nmol g-1 DW ± 171.8 ( ±95% CI) (Fig 3A; S4 File). Control, SMX, and DAN treatments concentration on day 2 were 1.6 to 1.8 times higher than the SMX and mixture treatment (p<0.05; Fig 3A; S4 File). At day 4, we saw that the mean control CO2 concentrations were now 1.4 times lower than the mixture treatment but this reduction was not significant (p>0.05; Fig 3A; S4 File). At day 7, we observed no significant differences in CO2 concentrations among treatments (p>0.05; Fig 3A). The increase in CO2 on day 7 compared to concentrations on day 2 suggests that as the microcosms became hypoxic or anoxic, CO2 production was promoted. Rate of CO2 production ranged from 20.4 to 68.4 nmol g-1 DW d-1 across treatments, with no difference across treatments (p>0.05; Fig 3B; Table 4).

Fig 3

Mean ± SE dissolved (A) CH4, (C) CO2 concentrations in microcosms plotted across time (Day 2, 4, and 7) and whisker plots (min to maximum) of the rate of production for (B) CH4 and (D) CO2 from microcosms exposed to control and experimental treatments.

CH4

Mean CH4 concentrations at day 2 ranged from 4.8 to 16.1 nmol g-1 DW ± 3.24 ( ±95%CI) (Fig 3C; S4 File). Control treatment concentration at day 2 (4.8 ± 0.5 nmol g-1 DW) was 1.6 to 3.4 times higher than the single and mixture antibiotic treatments (p<0.05; Fig 3A; S4 File). At day 4, control, DAN, and ETM treatment concentrations were 1.7 to 2.5 times lower than then SMX and mixture treatments (p<0.05; Fig 3C; S4 File). At the conclusion of the study on day 7, there was no difference in CH4 concentrations across treatments (Fig 3C; S4 File). Over the 7-day assay, CH4 concentrations increased in all treatments at rates ranging from 3.3 to 7.5 nmol g-1 DW d-1, with no significant difference across treatments compared to the controls (p>0.05; Table 4; Fig 3D).

Functional gene abundance

Mean number of copies of respective genes ranged from 1.86E+05 to 1.56E+06 copies per gram of sediment (S5 File). We observed no difference in copy number abundances for each respective gene. Correlation analysis revealed there was no significant correlation between functional genes and the rates of consumption or production respective genes are responsible for.

Discussion

In our assessment we initially expected to find that all antibiotic treatments would lead to declines in the assimilation and transformation of one or more forms of inorganic N and organic C relative to the controls. We anticipated the greatest impact to be seen in the mixture treatment due to the unknown interactions of these compounds possibly resulting in an additive or synergistic effect. However, at the conclusion of the present study we found that there were generally no differences pertaining to the impact antibiotics (both single and mixture exposures) posed on nutrient assimilation and transformation compared to control or antibiotic free treatments. The only assessment where we saw the mixture treatment behave differently than the control was in the rates of NH4+ uptake in our oxic assay.

Ecological assessments that include contaminant mixtures are highly underrepresented in environmental science. Although mixtures are a more realistic representative of the natural environment, the mechanisms behind their combined impact is complex due to varying modes of actions whose interaction is not widely understood. Chen et al. [42] and González-Pleiter et al. [43] both reported that mixtures of contaminants (pesticides and antibiotics), can result in a synergistic growth inhibition on photosynthetic aquatic organisms. The mixture used in the present study represented different antibiotic classes that each have a unique action mechanism (Table 2). The increase in NH4+ as a result of exposure to antibiotic mixtures is a topic that warrants further discussion.

We saw no change in NH4+ concentration in the SMX treatment during the oxic assay, which could be the result of SMX either inhibiting nitrification or enhancing mineralization. Nitrification inhibition by sulfonamides, such as SMX has been previously reported by [44]. The difference in antibiotic effect on nitrification can be influenced by whether it is a broad or narrow-spectrum antibiotic [45], where narrow spectrum can kill or inhibit a specific species, as opposed to broad spectrum that can target both gram-negative and positive bacteria (nitrifiers are gram-positive). However, each antibiotic used in the study was a broad-spectrum antibiotic, suggesting that effects on nitrification are not consistent or universal across all broad-spectrum drugs. We observed no effect of DAN or ETM treatments on NH4+ uptake when compared to the control treatment. However, the effects of the DAN+ETM+SMX treatment was distinct from the SMX alone treatment, indicating the potential for a synergistic effect for one or both antibiotics in combination with SMX.

The most interesting result from this experiment was the significant increase in NH4+ from the mixture treatment. Exposure to antibiotics can affect community functions such as mineralization [46]. These findings from the mixture treatment suggest both potentially enhanced mineralization and reduced nitrification as factors contributing to the increase in NH4+ over time. We cannot distinguish between these two possible mechanisms but our results suggest future work should focus on how antibiotic exposure may influence these two processes.

Based on NO3- consumption along with N2O and N2 production rates, it does not appear that antibiotic treatments, whether single or mixture, had any negative effect on denitrification. Underwood et al. [25] showed that SMX altered or inhibited denitrification at a concentration of 1.2 μg/L, a concentration almost 10 times lower than what was used in the present study. The different outcomes are likely a result of different experimental designs/exposures. Underwood et al. [25] used bacterial enrichment cultures from groundwater samples and exposed the isolated denitrifying community to SMX with no sediment. The impact of SMX and the other antibiotic treatments used in the present study may be less pronounced due to the presence of sediment and/or the microbial populations that colonized sediment, potentially neutralizing antibiotics. SMX is made up of weak forces that favor desorption rather than sorption [47]. Antibiotics that bind to sediment can result in reduced bioavailability and potency, making them less effective at inhibiting bacterial community growth [48, 49]. While the reduced bioavailability may be a factor here, sediment used in the study had relatively low percent organic matter content (Table 1). It is possible that low sorption capabilities resulted in microbes being less effected by antibiotics.

The lack of differences observed may have been influenced by microbes within each microcosm acclimating or proving to be resistant to antibiotics [50]. By resistance we mean that for a majority of our endpoints measured, they were not altered as a result of antibiotic exposure. It is also important to note that the minimum inhibitory concentrations (MIC) of SMX, ETM, and DAN range between 0.25 to 16 μg/ml which is the equivalent of 250 to 16000 μg/L, concentrations higher than what was used in the present study [51-53]. Due to utilizing concentrations below MICs reported in literature, findings may be the result of concentrations not being high enough to produce a varying effect from the control (excluding SMX and mixture impact on NH4+). It is worth noting that antibiotic resistance occurs naturally in nature [54]. The sediment bacterial communities may have already had resistance that resulted in antibiotics having no effect on nitrification (excluding SMX and mixture), denitrification, and methanogenesis.

Rossi et al. [55] reported that fluctuations in gene expression can inform the future outcomes of a variety of cellular states. When functional gene abundance was evaluated, we observed no difference in gene copy numbers of the functional genes across treatments, supporting our previous claims that acclimation or microbial resistance occurred. This finding is consistent with findings from [56], where when multiple studies assessed the relationship between gene abundance and end-products, only 38% showed that the concentration of products or reactants correlated with gene abundance. Although levels used in the present study are below MICs previously reported, bacterial responses to antibiotics can be ununiformed and vary across times [55], where as a result of exposure, communities that persist initial exposures can express genes higher to compensate for those potentially lost. Rocca et al. [56] recommended using metagenomic assessments of protein encoding genes as viable step in future studies. However, since our study found that end products and gene expression did not differ across treatments, utilizing metatranscriptomics in follow up work would be a proactive approach, allowing for a functional profile to be compiled based on genes expressed that are specific to biogeochemical processes of interest.

This study’s novelty was the paired evaluation of mixture exposure toxicity alongside single exposure toxicity in naïve stream sediments. Similar work has been conducted to in marine and wetland sediments, although streams are underreported [50, 57]. It is also important to note that these types of assessments rarely utilize environmentally relevant concentrations [50, 58]. Instead, previous work in the literature has focused on using therapeutic doses (mg/L or mg/kg) [59]. Demonstrating differences in mixture compared to single exposures are necessary as they more accurately reflect the natural environment. The mixture effect on nitrification is particularly interesting due to its importance in N cycling. In the present study we were able to address the question regarding how stream microbes respond to continuous exposure to antibiotics. However, stream organisms are exposed to both continuous and episodic exposures, largely influenced by runoff and wastewater effluent release [60]. Episodic or pulse exposures may affect toxicokinetic processes that result in varying results than what was found in the present study due to fluctuating concentrations that may be below or higher than MICs depending on design and relevance to study areas. Evaluating these exposure pathways would also provide more evidence into whether microbial communities and resistant to antibiotic exposure in certain study areas.

Nitrification of NH4+ to NO3- is an environmental concern due to excess NO3- leaching into groundwater (potential drinking water hazard), eutrophication, and its acute toxicity associated with wildlife. Any inhibition or reduction of the nitrification process, as demonstrated by the SMX and mixture treatments, can be seen as a positive regarding regulating NO3- in freshwaters. The potential of enhanced mineralization suggest that naïve stream sediments exposed to mixtures may experience greater bioavailability of nutrients within the system. The antibiotics used here are simply a small representation of the contaminants present in stream ecosystems. Moving forward it would be of interest to evaluate more emerging contaminants to determine how or whether nitrification is altered.

Freshwater systems globally are plagued with various synthetic chemicals entering at varying rates. Mixture assessments are vastly underrepresented and as the present study shows, in the case of nitrification, its effect can differ when compared to results from single exposures. Although there were not many differences observed between single and mixtures, future work into these dynamics are warranted due to the varying rates of introduction and concentrations of synthetic chemicals providing pressure on microbial communities. Stream microbes from the present study appear to be resistant to antibiotic pressure in some cases. However, there may be sublethal effects aside from alterations to biogeochemical cycling that are not fully understood and require further investigation.

Sediment information.

Sediment particle size composition of stream sediment.

(PDF)

Click here for additional data file.

Sediment oxygen demand.

Sediment oxygen levels from ambient and nutrient enrichment.

(PDF)

Click here for additional data file.

NH4+ and NO3- concentrations.

Mean ± SE NH4+ and NO3- concentrations at each sampling point.

(PDF)

Click here for additional data file.

N2O, N2, CH4, CO2 concentrations.

Mean ± SE concentrations of N2O, N2, CH4, and CO2 from each experimental treatment over the 7-day study.

(PDF)

Click here for additional data file.

Functional gene abundance.

Mean gene copy number per gram of sediment for each functional gene investigated in the study.

(PDF)

Click here for additional data file.

8 Nov 2021

PONE-D-21-30040Are Nitrogen and Carbon Cycle Processes Impacted by Common Stream Antibiotics? A Comparative Assessment of Single vs. Mixture ExposuresPLOS ONE

Dear Dr. Gray,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 23 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

John J. Kelly

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf  and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

3. Thank you for stating the following financial disclosure:

“AG

SETAC Student Exchange Training Opportunity

https://awards.setac.org/student-training-exchange-opportunity/

No”

Please state what role the funders took in the study.  If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

4. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I have reviewed the manuscript “Are nitrogen and carbon cycle processes impact by common stream antibiotics? A comparative assessment of single vs. mixture exposures” submitted for consideration of publication at PLOS One. The authors report results of a stream sediment incubation study assessing impacts of sulfamethoxazole, danofloxacin, and erythromycin singly and in combination on microbiological activities. Only ammonium uptake was affected, in that it was reduced with sulfamethoxazole, and switched to production with the combination of all 3 compounds. The manuscript is generally well written and easy to read, however there are several typos and misplaced or missing commas that should be paid close attention to on the final edit. I request few modifications to the content, however I do request more substantive discussion on the synergistic mechanisms at play in the ammonium release results, and more thought on cellular processes when discussing lack of differences or processes more likely to be affected. Please consider all the comments as detailed below in a revision.

Title: “impacted” instead of “impact”

L85: “irreversibly bind”

L87: “is a synthetic”

L89: delete “enzyme of”; “Prior environmental studies”

L115: “In the laboratory, ash-free dry mass”

L143: is this the correct formatting for Figure reference?

L179: MIMS

L227: “spiked”

L238 and all Figures: There are no post-hoc letters on the figures in my downloaded pdf. Please make sure these come through; it’s harder to interpret without them.

L296: note in text “copies per gram sediment”

L305-306: the wording on this statement needs to be fixed, and clarified

L327: “in” instead of “from”.

L327-332: The consideration of additive vs. synergistic effects in the discussion was intriguing. Please revisit that here. I expect the authors don’t want to get too speculative but there is an observation about reduced uptake vs. cell death that is possible. It would be even more interesting to do a back-of the envelope calculation of how many bacteria would have died to produce this much ammonium over a day….

L335 and L337: Start these sentences with Underwood et al. [26] instead of a number

L341: sorption of organic compounds is likely a major mechanism underlying apparent resistance or resilience, please add more emphasis and consideration here. Is the resistance/resilience biological, or only apparent due to physical buffering – would there be a threshold where chronic effects manifest?

L344: please don’t imply that evolutionary processes were happening over a day or a week (unless that is what is meant and if so needs to be substantiated); delete “adapting to or”, replace with “acclimating” if desired

L344 and L345: Sentences should not begin with “This”: specify what the subject is.

L344: Re lack of differences: are sulfamethoxazole, danofloxacin, and erythromycin anaerobe-effective? Also, antibiotic resistance exists in plenty of populations even in “naïve” sediments: many bacteria compete with one another, like all organisms.

L346-348: This is true but it would be more interesting to elaborate on the cellular mechanism: Unless cells are killed and the DNA decomposed, there will be no decline in gene copies; but in the short term cellular functions including reproduction should be inhibited. In fact, the same would apply to metagenomic assessment so I don’t agree with the viability of metagenomics as a next step as posed in L349. Considering which bacterial populations are fastest-growing and which biogeochemical functions they support might be more interesting in this paragraph.

L373-374: This sentence could benefit from some grammatical attention (who are “they”- and there are two different implied subjects, one in each question listed, neither subject is stated directly) and also some elaboration on what is meant by “cost”. Please improve this statement.

Supplemental Table 3: There is a lingering comment in the document, please fix.

Authors are required to make raw data publicly available, if I understand correctly, and I do not see a link to data repository in the manuscript.

Reviewer #2: This manuscript describes the results of an experiment where a stream sediment microbial community with little prior exposure to antibiotics was exposed to low levels of antibiotics. The authors were seeking to understand more about how antibiotics given to humans and animals and subsequently released into wastewater and then receiving streams could impact the ecosystem-related functions of microorganisms in those streams. Laboratory microcosms were set up to expose the sediment to one of three antibiotics or to a mixture of the antibiotics. Nutrients also were added to the microcosms. The chemical and biological components of the microcosms were interrogated with numerous chemical and biological measurements over the course of a 7-day incubation. It was predicted that the antibiotics would have a significant reduction in the capability of the sediment community to conduct nitrogen transformations and uptake organic carbon. Ultimately the authors found that the antibiotics had fairly little impact on the functioning of these microbial communities. Nitrification may have been impacted during the oxic phase of the incubations (<24 hours) by the sulfonamide and mixed antibiotic treatments, but it was suggested further study would be needed to clarify this impact.

Overall, I found this to be a well conducted study and a cohesive manuscript. The results indicated that low levels of antibiotics over a short duration may not have a big impact on the nitrogen cycling or organic C uptake by the sediment microbial community in streams. This information will be useful in future work that addresses impacts of additional antibiotics/pharmaceuticals or varying concentrations of these substances on aquatic microorganisms and/or the ecosystem services provided by these systems. I do not have any major criticisms of the work, but I do have some minor points that need clarification and questions about some of the results interpretation presented in the discussion.

Also, please see the details regarding PLOS ONE data availability. A researchgate account is listed as the place where data is housed, but I did not see the underlying data upon going to that account. PLOS asks that all data used to calculate means, etc. are available in their raw count form. Please make these data available as supplemental info or in another data repository.

Specific comments

Throughout the manuscript there are some minor grammar issues – e.g. wrong tense or extra words to delete. The authors should look for and fix these small details; here are a few examples:

L85 – should be “binds” not “binding”

L95 – should be “common” not “commonly”

L227 – should be “spiked” not “spike”

L232 – delete “used”

L305 – should be “there” instead of “the”

L108 – What is meant by “for the assay” in this sentence? Is this the water that was collected for all the experimental setups? Please clarify.

L109-110 – Please cite this work, if possible, even if it is from a non-peer reviewed source. It would be useful to have the data showing that antibiotics are undetectable at this site – then the reader could evaluate what antibiotics were assayed and what method was used, etc.

L191 – This is semantics, but by convention it is written as the “16S rRNA gene” and is not italicized. Italics are used for protein-coding genes.

L312 – I agree that antibiotic mixtures are a more realistic scenario experienced by aquatic microbes, but how are the mechanisms behind their impact more complex than a single antibiotic exposure? Is there evidence that mixtures create a larger impact than would be predicted based on responses to individual antibiotics? Further support for this statement is needed or it needs to be presented as an opinion.

L314 – 318 – Could another alternative be that the concentration of antibiotic added was not at a level that would impact many microbes? What is the minimum inhibitory concentration for these antibiotics and how does this relate to the concentration used? Have other observed effects on microbial activity at these concentrations. If not, then it is possible that the dose was too low to impact process. I agree that low concentrations create a more realistic scenario, and the ones used here matched measured levels in other waterways, so it was a good target.

Perhaps a more continuous dosing of antibiotics, which could be brought by wastewater discharge would have a larger effect at this low concentration than a single pulse of the antibiotic. I believe additional discussion related to the antibiotic concentration used would aid in interpretation of the results.

Also in this section – in what evidence is there that these communities are highly resilient? My question isn’t whether the communities are resilient – this is a hypothesis, but more how are the authors defining that term. I tend to define it as the ability to recover from disturbance to a pre-disturbance state. This would indicate that at some point there was a big change in microbial community following antibiotic addition, but it recovered quickly. To me that data don’t support that as being a primary conclusion. I see it more that the community was resistant to this disturbance – i.e. they were not impacted or that there was enough redundancy in the community that it superseded any losses. A more specific indication of what is meant here by resilient would clarify what hypotheses the authors are considering in the interpretation of their data.

L317 – 318 – Why not discuss this here then? What do you think it means? Or what do you mean exactly by this statement?

L323 – In what way does being a broad or narrow spectrum antibiotic matter to nitrification? Be more specific in this statement.

L327 – come back to this any additional thoughts?

L340 - 342 – Clarify this. I think I agree with your point but make clear the distinction between the studies. Did the previous study also use sediment? Sediment inclusion could make a big difference as diffusion of the antibiotic into the sediment may not be that high in 7 days.

The wording, “…antibiotics exposed within sediment…” is a bit confusing. Is this stating that the antibiotics were added to the sediment or that the microbes in the sediment rather than the water were exposed to the antibiotics?

L343 – More explanation is needed in this paragraph? I do not follow the logic that the communities changed in structure, but this led to a lack of difference in measured gene copies. If the community composition is changing rapidly, I would expect the nitrogen-related gene concentrations to change rapidly as well, as only a few select taxa are capable of many of the relevant processes.

I agree with the reference cited that the concentration of a particular gene often does not relate to the activity levels at any given moment for that gene product. To get at this idea, gene expression (mRNA or protein copies) would need to be quantified. However, here the end products (N2 gas, etc.) were measured and they were similar between the control and treatment, so I would not expect that gene expression levels changed much either. I would suggest metatranscriptomics rather than metagenomics would be a better measure – find out which organisms are actually responding to the different microcosm setups.

L373 – 374 – The wording of this sentence is not clear. Please re-phrase. The negative, “…not how they are impacted…” make it difficult to interpret. Also, what is meant by “cost”? Is there a cost to the microbes for resisting antibiotics?

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

2 Dec 2021

Review Comments to the Author

The authors appreciate the thorough review of our submitted manuscript titled “Are nitrogen and carbon cycle processes impacted by common stream antibiotics? A comparative assessment of single vs. mixture exposures”. Below we have responded to specific reviewers’ comments and have included information as to where specific changes were made in the revised manuscript (identified by line number). We also adjusted the reference list to support information for in text revisions.

Reviewer 1 Overall comments on the manuscript

Reviewer #1: I have reviewed the manuscript “Are nitrogen and carbon cycle processes impacted by common stream antibiotics? A comparative assessment of single vs. mixture exposures submitted for consideration of publication at PLOS One. The authors report results of a stream sediment incubation study assessing impacts of sulfamethoxazole, danofloxacin, and erythromycin singly and in combination on microbiological activities. Only ammonium uptake was affected, in that it was reduced with sulfamethoxazole, and switched to production with the combination of all 3 compounds. The manuscript is generally well written and easy to read, however there are several typos and misplaced or missing commas that should be paid close attention to on the final edit. I request few modifications to the content; however, I do request more substantive discussion on the synergistic mechanisms at play in the ammonium release results, and more thought on cellular processes when discussing lack of differences or processes more likely to be affected. Please consider all the comments as detailed below in a revision.

Reviewer 2 overall comments on manuscript

Reviewer #2: This manuscript describes the results of an experiment where a stream sediment microbial community with little prior exposure to antibiotics was exposed to low levels of antibiotics. The authors were seeking to understand more about how antibiotics given to humans and animals and subsequently released into wastewater and then receiving streams could impact the ecosystem-related functions of microorganisms in those streams. Laboratory microcosms were set up to expose the sediment to one of three antibiotics or to a mixture of the antibiotics. Nutrients also were added to the microcosms. The chemical and biological components of the microcosms were interrogated with numerous chemical and biological measurements over the course of a 7-day incubation. It was predicted that the antibiotics would have a significant reduction in the capability of the sediment community to conduct nitrogen transformations and uptake organic carbon. Ultimately the authors found that the antibiotics had fairly little impact on the functioning of these microbial communities. Nitrification may have been impacted during the oxic phase of the incubations (<24 hours) by the sulfonamide and mixed antibiotic treatments, but it was suggested further study would be needed to clarify this impact.

Overall, I found this to be a well conducted study and a cohesive manuscript. The results indicated that low levels of antibiotics over a short duration may not have a big impact on the nitrogen cycling or organic C uptake by the sediment microbial community in streams. This information will be useful in future work that addresses impacts of additional antibiotics/pharmaceuticals or varying concentrations of these substances on aquatic microorganisms and/or the ecosystem services provided by these systems. I do not have any major criticisms of the work, but I do have some minor points that need clarification and questions about some of the results interpretation presented in the discussion.

Also, please see the details regarding PLOS ONE data availability. A researchgate account is listed as the place where data is housed, but I did not see the underlying data upon going to that account. PLOS asks that all data used to calculate means, etc. are available in their raw count form. Please make these data available as supplemental info or in another data repository

tory.

Authors general comments: Reviewers 1 & 2 each made comments specific to grammatical issues throughout the text. Those comments can be found below. We have gone through the document and made necessary changes to the text in reflection to their comments. Other edits can be found in the text and marked via track changes. Comments specific to grammar have been included below. Reviewers also commented on public data sharing. Raw data for this project can be found at https://doi.org/10.6084/m9.figshare.17008964.v1 https://doi.org/10.6084/m9.figshare.17009126.v1

Reviewer 1

Title: “impacted” instead of “impact”

L85: “irreversibly bind”

L87: “is a synthetic”

L89: delete “enzyme of”; “Prior environmental studies”

L115: “In the laboratory, ash-free dry mass”

L143: is this the correct formatting for Figure reference?

L179: MIMS

L227: “spiked”

L296: note in text “copies per gram sediment”

L305-306: the wording on this statement needs to be fixed, and clarified

L327: “in” instead of “from”.

L344 and L345: Sentences should not begin with “This”: specify what the subject is.

Changes to the text for this specific comment are reflected in the revised manuscript (L344-345)

L335 and L337: Start these sentences with Underwood et al. [26] instead of a number

Supplemental Table 3: There is a lingering comment in the document, please fix.

Reviewer 2

L85 – should be “binds” not “binding”

L95 – should be “common” not “commonly”

L227 – should be “spiked” not “spike”

L232 – delete “used”

L305 – should be “there” instead of “the”

L191 – This is semantics, but by convention it is written as the “16S rRNA gene” and is not italicized. Italics are used for protein-coding genes.

Reviewer 1 comments to address

Reviewer comment: L108 – What is meant by “for the assay” in this sentence? Is this the water that was collected for all the experimental setups? Please clarify.

Response: Thank you for commenting on this. Yes, the sediment and surface water that was collected from this forested stream were used in microcosm construction. We have revised the text to reflect these changes (L109)

Reviewer comment: L109-110 – Please cite this work, if possible, even if it is from a non-peer reviewed source. It would be useful to have the data showing that antibiotics are undetectable at this site – then the reader could evaluate what antibiotics were assayed and what method was used, etc.

Response: We regret to inform the reviewer that the data was not previously available in a source that is referenceable. To provide transparency we added the chromatograph to our open source repository at https://doi.org/10.6084/m9.figshare.17009126.v1 . Antibiotics were identified initially based on the [M+H] + ion m/z signature. In using MZmine software we found no ion masses or chemical structures that were reflective of the antibiotics utilized in the present study as well as those detailed in:

• Pugajeva, I., Rusko, J., Perkons, I., Lundanes, E., & Bartkevics, V. (2017). Determination of pharmaceutical residues in wastewater using high performance liquid chromatography coupled to quadrupole-Orbitrap mass spectrometry. Journal of pharmaceutical and biomedical analysis, 133, 64-74.

Reviewer comment: L238 and all Figures: There are no post-hoc letters on the figures in my downloaded pdf. Please make sure these come through; it’s harder to interpret without them.

Response: We have adjusted the figure to identify differences through specific details. As stated in the figure legends, the posthoc letters are only for the first figure rate graphs. Thus, you can find the letters only in figure since there were no other significant differences in other figures.

Reviewer comment: L327-332: The consideration of additive vs. synergistic effects in the discussion was intriguing. Please revisit that here. I expect the authors don’t want to get too speculative but there is an observation about reduced uptake vs. cell death that is possible. It would be even more interesting to do a back-of the envelope calculation of how many bacteria would have died to produce this much ammonium over a day….

Response: We love this suggestion and the reviewers enthusiasm for this really interesting problem of additive vs. synergistic effects. While we would love the freedom to speculate more wildly, our results just aren't giving enough insight to feel comfortable pushing this idea in the discussion. It was a major motivation of the entire study, but the effects of our treatments were too subtle to make any strong inferences. That's good news for sediment microbes, but doesn't push the mechanistic understanding as far as we would like. This will definitely be motivating future and more elegant experimental designs.

Reviewer comment: L341: sorption of organic compounds is likely a major mechanism underlying apparent resistance or resilience, please add more emphasis and consideration here. Is the resistance/resilience biological, or only apparent due to physical buffering – would there be a threshold where chronic effects manifest?

Response: Thank you for pointing this out as a topic that should be included. Sorption does play a role in the biological inactivity or activity of xenobiotics. However, we felt that this mechanism may not be as influential due to the percent organic matter for sediment being relatively low at 1.2% and sediment particles being more composed to course particles rather than fine, which would alter sorption as well. We did include information in the revision pertaining to the physicochemical properties of antibiotics and how their interaction with sediment may favor sorption or desorption which may influence their biological activity in sediments and our results. Changes to the text can be found on L342.

We also included information on the results also being attributed to the MIC for each antibiotic used (0.25 to 16 ug/ml or 250 to 16000 ug/L), thus, indicating that levels used may not have been high enough to promote a biological response.

Reviewer comment: L344: please don’t imply that evolutionary processes were happening over a day or a week (unless that is what is meant and if so needs to be substantiated); delete “adapting to or”, replace with “acclimating” if desired

Response: We appreciate this comment and suggestion. We have revised the text to not include misleading statements.

Reviewer comment: L344: Re lack of differences: are sulfamethoxazole, danofloxacin, and erythromycin anaerobe-effective? Also, antibiotic resistance exists in plenty of populations even in “naïve” sediments: many bacteria compete with one another, like all organisms.

Response: We appreciate this comment, previous work (referenced below) has shown that anaerobic bacteria are susceptible to antibiotics used in the study.

• SMX (Wüst, J., & Wilkins, T. D. (1978). Susceptibility of anaerobic bacteria to sulfamethoxazole/trimethoprim and routine susceptibility testing. Antimicrobial agents and chemotherapy, 14(3), 384-390.)

• ETM (Watt, B. (1977). Erythromycin and anaerobes: in vitro aspects. Scottish medical journal, 22(1_suppl), 389-391.), and for

• DAN (Papich, M. G., & Watts, J. L. (2017). New interpretive criteria for danofloxacin antibacterial susceptibility testing against Mannheimia haemolytica and Pasteurella multocida associated with bovine respiratory disease. Journal of veterinary diagnostic investigation, 29(2), 224-227.

Reviewer comment: L346-348: This is true but it would be more interesting to elaborate on the cellular mechanism: Unless cells are killed and the DNA decomposed, there will be no decline in gene copies; but in the short-term cellular functions including reproduction should be inhibited. In fact, the same would apply to metagenomic assessment so I don’t agree with the viability of metagenomics as a next step as posed in L349. Considering which bacterial populations are fastest-growing and which biogeochemical functions they support might be more interesting in this paragraph.

Response: We appreciate the reviewers’ comments and have put more emphasis in to follow-up analysis that would benefit these types of studies, particularly moving from metagenomics to metatranscriptomics to create a functional profile of genes expressed that are specific to biogeochemical processes. Revised text for this can be found on L373-378.

Reviewer comment: L373-374: This sentence could benefit from some grammatical attention (who are “they”- and there are two different implied subjects, one in each question listed, neither subject is stated directly) and also some elaboration on what is meant by “cost”. Please improve this statement.

Response: Thank you for your comment, we initially were trying to convey that although microbes seem to be resistant to pressure from antibiotics, there may be other measurable endpoints that are impacted that scientist have not accounted for, warranting future work to understand more how mixtures effect these communities. We have made edits to that section of the discussion to provide clarity, improved grammar, and a more thoughtful conclusion.

Reviewer comment: Authors are required to make raw data publicly available, if I understand correctly, and I do not see a link to data repository in the manuscript.

Response: We have uploaded the raw data and additional tables to figshare (https://figshare.com/articles/dataset/_/17008964).

Reviewer 2 Comments to Address

Reviewer comment: L312 – I agree that antibiotic mixtures are a more realistic scenario experienced by aquatic microbes, but how are the mechanisms behind their impact more complex than a single antibiotic exposure? Is there evidence that mixtures create a larger impact than would be predicted based on responses to individual antibiotics? Further support for this statement is needed or it needs to be presented as an opinion.

Response: Thank you for your comment, we have made revisions in the document to reflect these changes. The rationale for the text is due to the potential for mixtures to act in ways that differs from single exposure. While the references in the text are specific to cyanobacteria, we believe it is still relative to the overall subject of mixture toxicity vs single. Revised changes can be found on L312-L315

Reviewer comment: L314 – 318 – Could another alternative be that the concentration of antibiotic added was not at a level that would impact many microbes? What is the minimum inhibitory concentration for these antibiotics and how does this relate to the concentration used? Have other observed effects on microbial activity at these concentrations. If not, then it is possible that the dose was too low to impact process. I agree that low concentrations create a more realistic scenario, and the ones used here matched measured levels in other waterways, so it was a good target.

Response: Another reviewer mentioned this as well. We have added in additional text, references, and elaboration in the discussion to address this (L353-357).

Reviewer comment: Perhaps a more continuous dosing of antibiotics, which could be brought by wastewater discharge would have a larger effect at this low concentration than a single pulse of the antibiotic. I believe additional discussion related to the antibiotic concentration used would aid in interpretation of the results.

Response: Thank you, we believe that is a great idea. We added additional text specific to follow up studies and utilizing pulses rather than continuous exposure, which mimic antibiotic occurrence in the natural environment, specifically urban streams that receive effluent. Revised text can be found at (L389-392).

Reviewer comment: Also in this section – in what evidence is there that these communities are highly resilient? My question isn’t whether the communities are resilient – this is a hypothesis, but more how are the authors defining that term. I tend to define it as the ability to recover from disturbance to a pre-disturbance state. This would indicate that at some point there was a big change in microbial community following antibiotic addition, but it recovered quickly. To me that data don’t support that as being a primary conclusion. I see it more that the community was resistant to this disturbance – i.e. they were not impacted or that there was enough redundancy in the community that it superseded any losses. A more specific indication of what is meant here by resilient would clarify what hypotheses the authors are considering in the interpretation of their data. L317 – 318 – Why not discuss this here then? What do you think it means? Or what do you mean exactly by this statement?

Response: Thank you for a thoughtful comment, we have taken this into consideration and have removed text in this area and revised this topic so that is later discussed in the manuscript on (L353-363)

Reviewer comment: L323 – In what way does being a broad or narrow spectrum antibiotic matter to nitrification? Be more specific in this statement.

Response: We have taken this comment into consideration and added additional text to clarify the intent. In short, narrow spectrum targets a specific group of bacteria, while broad targets both gram negative and positive bacteria. Nitrifiers are typically gram positive and each antibiotic used was a broad spectrum, demonstrating that although they may be classified as broad spectrum, their impact on processes such as nitrification can vary (L323-327).

Reviewer comment: L340 - 342 – Clarify this. I think I agree with your point but make clear the distinction between the studies. Did the previous study also use sediment? Sediment inclusion could make a big difference as diffusion of the antibiotic into the sediment may not be that high in 7 days.

Response: Thank you, for clarification that study referenced did not use sediment. We have reflected this change in the revised text (L341-351)

Reviewer comment: The wording, “…antibiotics exposed within sediment…” is a bit confusing. Is this stating that the antibiotics were added to the sediment or that the microbes in the sediment rather than the water were exposed to the antibiotics?

Response: We have revised the text in the section to clarify our rationale and line of thought. (L345)

Reviewer comment: L343 – More explanation is needed in this paragraph? I do not follow the logic that the communities changed in structure, but this led to a lack of difference in measured gene copies. If the community composition is changing rapidly, I would expect the nitrogen-related gene concentrations to change rapidly as well, as only a few select taxa are capable of many of the relevant processes (L355-360).

Response: We agree with the reviewer that our initial version included logic that did not tie in together with our findings. We revised the text to include more information on MICs of antibiotics and the possibility of concentrations being too low to observe an effect along with natural resistance that microbial communities develop even when not exposed to antibiotics that may have negated any effects.

Reviewer comment: I agree with the reference cited that the concentration of a particular gene often does not relate to the activity levels at any given moment for that gene product. To get at this idea, gene expression (mRNA or protein copies) would need to be quantified. However, here the end products (N2 gas, etc.) were measured and they were similar between the control and treatment, so I would not expect that gene expression levels changed much either. I would suggest metatranscriptomics rather than metagenomics would be a better measure – find out which organisms are actually responding to the different microcosm setups.

Response: We have looked into this more and added specific text explaining why metagenomic may be limited in these types of studies and how metatranscriptomics would benefit future studies. Revised text can be found at (L373-378)

Reviewer comment: L373 – 374 – The wording of this sentence is not clear. Please re-phrase. The negative, “…not how they are impacted…” make it difficult to interpret. Also, what is meant by “cost”? Is there a cost to the microbes for resisting antibiotics?

Response: This was also addressed in Reviewer 1 comments and the closing of the discussion has been revised to remove any text that was previously hard to interpret.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

9 Dec 2021

Are Nitrogen and Carbon Cycle Processes Impacted by Common Stream Antibiotics? A Comparative Assessment of Single vs. Mixture Exposures

PONE-D-21-30040R1

Dear Dr. Gray,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

John J. Kelly

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

14 Dec 2021

PONE-D-21-30040R1

Are nitrogen and carbon cycle processes impacted by common stream antibiotics? A comparative assessment of single vs. mixture exposures

Dear Dr. Gray:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. John J. Kelly

Academic Editor

PLOS ONE